Title

Author

Date

May 2010

Document Type

Thesis

Degree Name

M.S.

Department

Dept. of Medical Informatics and Clinical Epidemiology

Institution

Oregon Health & Science University

Abstract

Gene expression profiles and mass-spectrometry analysis of a plaque have revealed genes and proteins involved in an atherosclerotic plaque progression. Though differentially expressed genes in an atherosclerotic plaque progression have been identified previously, this is the first study that has combined gene expression data with proteins identified from different stages of plaque progression to identify pathways and candidate genes affecting state of a plaque using a network approach. We constructed an unstable plaque network with 59 genes of which 9 were transcription factors, 10 genes were over expressed and 12 genes were under expressed. Of all genes and proteins found to be associated with a plaque progression, we further identified and prioritized candidate genes which could be potential biomarker or drug targets to prevent progression of a plaque. In this study we also show that just differential expression of genes does not identify genes which are associated with the disease s

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